气候变化领域集成服务门户(CCPortal): Exploring Sources of Surface Bias in HRRR Using New York State Mesonet

CCPortal

DOI	10.1029/2021JD034989
	Exploring Sources of Surface Bias in HRRR Using New York State Mesonet
	Min L.; Fitzjarrald D.R.; Du Y.; Rose B.E.J.; Hong J.; Min Q.
发表日期	2021
ISSN	2169-897X
卷号	126 期号:20
英文摘要	In recent years, there has been increasing demand for applications of short-term forecasting of renewable energy potential and assessments of the likelihood of extreme weather events using the High-Resolution Rapid Refresh (HRRR) model. Examining the biases in the newest version of HRRR is necessary to promote further model development. Using data from one of the most comprehensive and dense monitoring networks, New York State Mesonet (NYSM), we evaluate the HRRR version 3 meteorological fields for an entire year. In this work, the land-atmosphere-cloud coupling system is evaluated as an integrated whole. We investigate the physical processes influencing the soil hydrological balance and the thermodynamic interactions, from surface fluxes up to the level of boundary layer convection from both temporal (seasonal and diurnal) and spatial perspectives. Results show that the model 2 m temperature and humidity biases are seasonally dependent, with warm and dry bias present during the warm season, and an extreme nocturnal cold bias in winter. The summer warm bias includes both a land-surface-induced bias and a cloud-induced bias. Inaccurate representation of energy partition and soil hydrological process across different land use types as well as a hydrological bias in describing spring snowmelt are identified as the main source of the land-surface-induced bias. A feedback loop linking cloud presence, flux changes, and temperature contributes to the cloud-induced bias. The positive solar radiation bias increases from clear sky to overcast sky conditions. The most significant bias occurs during overcast and thick cloud conditions associated with frontal passage and thunderstorms. © 2021. American Geophysical Union. All Rights Reserved.
英文关键词	cloud; HRRR model evaluation; New York State Mesonet; soil moisture; surface energy balance
来源期刊	Journal of Geophysical Research: Atmospheres
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/236951
作者单位	Atmospheric Sciences Research Center, University at Albany, Albany, NY, United States; Department of Atmospheric and Environmental Sciences, University at Albany, Albany, NY, United States; State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China
推荐引用方式 GB/T 7714	Min L.,Fitzjarrald D.R.,Du Y.,et al. Exploring Sources of Surface Bias in HRRR Using New York State Mesonet[J],2021,126(20).
APA	Min L.,Fitzjarrald D.R.,Du Y.,Rose B.E.J.,Hong J.,&Min Q..(2021).Exploring Sources of Surface Bias in HRRR Using New York State Mesonet.Journal of Geophysical Research: Atmospheres,126(20).
MLA	Min L.,et al."Exploring Sources of Surface Bias in HRRR Using New York State Mesonet".Journal of Geophysical Research: Atmospheres 126.20(2021).